Featurizing Koopman Mode Decomposition

arXiv:2312.09146v3 Announce Type: replace-cross
Abstract: This article introduces an advanced Koopman mode decomposition (KMD) technique -- coined Featurized Koopman Mode Decomposition (FKMD) -- that uses time embedding and Mahalanobis scaling to enhance analysis and prediction of high dimensional dynamical systems. The time embedding expands the observation space to better capture underlying manifold structure, while the Mahalanobis scaling, applied to kernel or random Fourier features, adjusts observations based on the system's dynamics. This aids in featurizing KMD in cases where good …

abstract advanced analysis article arxiv embedding manifold math.ds math.mp math-ph observation prediction scaling space stat.ml systems type